Triple

T10080853
Position Surface form Disambiguated ID Type / Status
Subject Chapel Bridge E213895 entity
Predicate hasView P854 FINISHED
Object Lake Lucerne E162352 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lake Lucerne | Statement: [Chapel Bridge, hasView, Lake Lucerne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Lucerne
Context triple: [Chapel Bridge, hasView, Lake Lucerne]
  • A. Lake Lucerne chosen
    Lake Lucerne is a picturesque, fjord-like lake in central Switzerland, renowned for its dramatic mountain scenery, historic sites, and role as a major tourist destination.
  • B. Lake Thun
    Lake Thun is a large alpine lake in the Bernese Oberland region of Switzerland, renowned for its scenic mountain backdrop, historic lakeside towns, and popular boating and water sports.
  • C. Lake of Biel
    Lake of Biel is a scenic lake in western Switzerland’s Seeland region, known for its vineyards, islands, and role in the Jura water correction system.
  • D. Lake Brienz
    Lake Brienz is a deep, turquoise-colored alpine lake in central Switzerland, renowned for its dramatic mountain scenery and crystal-clear waters.
  • E. Lake Sarnen
    Lake Sarnen is a scenic alpine lake in the canton of Obwalden in central Switzerland, known for its clear waters and surrounding mountain landscapes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd032ef288190a961d266d9ecafbc completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b660987c8190a6a29d9e56acbff7 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.